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Self-Taught to Systematic Algorithmic Trading | Venkatesh C L | QuantInsti EPAT Review
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ticker lesson
Breakdown
0:01lesson
Introduction to trading through father's influence
- Trading introduced via father's manual trades
- Curiosity led to YouTube and courses
- Discovered platform called traum
- Transition to algorithmic trading via quantine
2:07lesson
Challenges in backtesting and algorithmic trading
- Backtesting issues with broker data
- Expensive to hire developers for custom strategies
- Need to tweak hypotheses frequently
- AI tools like EPAD filled the gap
4:10lesson
Statistical analysis and portfolio diversification
- Implementing statistical analysis in real time
- Using ML models for pattern identification
- Portfolio risk management module
- Visualization of over-diversification risks
6:04lesson
Course content and faculty expertise
- Faculty knowledge in real trading scenarios
- Structured learning modules
- Suggestions for improving options data access
- Course helped in structured thinking
8:10lesson
AI assistance and strategy development
- AI provides relevant modules for stuck concepts
- Helped in tweaking strategy
- Testing with small capital before scaling
- Uncertainty in algorithmic trading sustainability
10:07lesson
Portfolio performance and future goals
- 35% return on portfolio vs benchmarks
- 20% alpha achieved
- Zeroda portfolio performance
- Next target: F1 trading
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